BUSINESS INTELLIGENCE STRATEGY AND VISION
BI / ANALYTICS PROJECT MANAGEMENT
SAP HANA VORA
BIG DATA - HADOOP
APPLICATION MANAGEMENT SERVICES
Work with engineering and research teams on designing, building and deploying data analysis systems for large data sets.
Create/use Machine Learning algorithms to extract information from large data sets for pattern discovery leveraging Apache Spark and MLlib APIs (preferably in Scala or Python).
Establish scalable, efficient, automated processes for model development, model validation, model implementation and large scale data analysis.
Develop metrics and prototypes that can be used to drive business decisions.
Provide thought-leadership and dependable execution on diverse projects.
Identify emergent trends and opportunities for future client growth and development.
Work with team leaders and members to solve client analytics problems and document results and methodologies.
Provide a business metrics for the overall project to show improvements (contribution to the improvement should be monitored initially and over multiple iterations).
Provide on-going tracking and monitoring of performance of decision systems and statistical models.
Lead the design and deployment of enhancements and fixes to systems as needed.
Bachelor degree in mathematics, statistics or computer science or related field; Master degree preferred.
Typically requires 3-5 years of relevant quantitative and qualitative research and analytics experience.
Solid knowledge of statistical techniques.
The ability to come up with solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets.
Strong programming skills (such as Scala, Spark, MLlib or other big data frameworks and Python), and statistical modeling (like SAS or R).
Experience with common data science toolkits, such as R, Weka, NumPy, MatLab.
Experience in data visualization tools like Apache Zeppelin, Tableau.
Proficiency in querying languages like Hive, PIG, SQL.
Experience in SAP HANA, SAP HANA Vora is highly preferable.
Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc.
Proficiency in the use of statistical packages.
Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms.
Strong communication and interpersonal skills.
Knowledge of one or more business/functional areas.
Demonstrable ability to quickly understand new concepts-all the way down to the theorems- and to come out with original solutions to mathematical issues.
Good communication and interpersonal skills.
Knowledge of one or more business/functional areas
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